Topics for: GENERATIVE ARTIFICIAL INTELLIGENCE AND THE FUTURE OF FINANCIAL FORECASTING: EVIDENCE FROM LARGE LANGUAGE MODELS

Focus on the unique opportunity of Generative AI to analyze massive amounts of unstructured data (like news articles, social media sentiment, and earnings call transcripts). How does combining this qualitative data with traditional financial numbers lead to more robust and accurate market predictions?

Explore the major risks of integrating Generative AI into financial forecasting. How do issues like "hallucination" (the AI making up facts), data privacy leaks, and lack of transparency (explainability) create significant governance and trust challenges for financial institutions and regulators?

Discuss the direct evidence: can Large Language Models (LLMs) like GPT-4o actually beat human financial analysts or traditional statistical models in forecasting stock prices, earnings, and market trends? Where does the LLM excel (e.g., handling unstructured data) and where does it fail?